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Nowadays, the latest generation of collaborative filtering methods still requires further improvements to make the recommendations more efficient and accurate. Therefore, the objective of this article is to propose a new effective recommender system for TED talks that first groups users according to their preferences, and then provides a powerful mechanism to improve the quality of recommendations for users. In this context, the authors used the Pearson Correlation Coefficient (PCC) method and TED talks to create the TED user-user matrix. Then, they used the k-means clustering method to group the same users in clusters and create a predictive model. Finally, they used this model to make relevant recommendations to other users. The experimental results on real dataset show that their approach significantly outperforms the state-of-the-art methods in terms of RMSE, precision, recall, and F1 scores.<\/jats:p>","DOI":"10.4018\/ijitwe.2020010103","type":"journal-article","created":{"date-parts":[[2019,11,4]],"date-time":"2019-11-04T13:29:02Z","timestamp":1572874142000},"page":"35-51","source":"Crossref","is-referenced-by-count":10,"title":["An Effective Recommender System Based on Clustering Technique for TED Talks"],"prefix":"10.4018","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4652-9121","authenticated-orcid":true,"given":"Faiz","family":"Maazouzi","sequence":"first","affiliation":[{"name":"University of Souk Ahras, Souk Ahras, Algeria"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9441-4842","authenticated-orcid":true,"given":"Hafed","family":"Zarzour","sequence":"additional","affiliation":[{"name":"University of Souk Ahras, Souk Ahras, Algeria"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yaser","family":"Jararweh","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Jordan University of Science and Technology, Irbid, Jordan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"2432","reference":[{"key":"IJITWE.2020010103-0","unstructured":"Pham, M. 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